Upload 6 files

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model_code1.keras filter=lfs diff=lfs merge=lfs -text
+static/uploads/That's[[:space:]]the[[:space:]]One[[:space:]]-[[:space:]]Ryan[[:space:]]McCaffreyGo[[:space:]]By[[:space:]]Ocean.mp3 filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,118 @@
+from flask import Flask, render_template, request, redirect, url_for
+import os
+import librosa
+import numpy as np
+import tensorflow as tf
+from sklearn.preprocessing import StandardScaler
+import pickle
+import subprocess  # Untuk menjalankan perintah FFmpeg
+import threading  # Untuk menjalankan penghapusan otomatis file setelah delay
+
+app = Flask(__name__)
+
+# Path folder untuk menyimpan file yang diunggah
+UPLOAD_FOLDER = 'static/uploads'
+app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
+
+# Load model dan scaler
+model = tf.keras.models.load_model('model_code1.keras')
+with open('scaler.pkl', 'rb') as f:
+    scaler = pickle.load(f)
+
+# Label genre musik
+genres = ['blues', 'classical', 'country', 'disco', 'hiphop', 'jazz', 'metal', 'pop', 'reggae', 'rock']
+
+# Fungsi untuk menghapus file setelah delay
+def delete_file_after_delay(file_path, delay=3600):
+    def delete_file():
+        try:
+            if os.path.exists(file_path):
+                os.remove(file_path)
+                print(f"File {file_path} berhasil dihapus setelah {delay} detik.")
+        except Exception as e:
+            print(f"Gagal menghapus file {file_path}: {e}")
+
+    # Jalankan penghapusan file dalam thread baru
+    threading.Timer(delay, delete_file).start()
+
+# Fungsi untuk mengonversi MP3 ke WAV menggunakan FFmpeg
+def convert_mp3_to_wav(mp3_path):
+    wav_path = mp3_path.replace('.mp3', '.wav')  # Ubah ekstensi ke .wav
+    try:
+        # Jalankan perintah FFmpeg untuk konversi
+        subprocess.run(['ffmpeg', '-i', mp3_path, wav_path], check=True)
+        # Hapus file MP3 setelah berhasil dikonversi
+        os.remove(mp3_path)
+        return wav_path
+    except subprocess.CalledProcessError as e:
+        print(f"Error converting MP3 to WAV: {e}")
+        return None
+    except OSError as e:
+        print(f"Error deleting MP3 file: {e}")
+        return None
+
+# Fungsi untuk ekstraksi fitur dari file musik
+def extract_features(file_path):
+    try:
+        y, sr = librosa.load(file_path, duration=30, sr=22050)
+
+        # Ekstraksi fitur
+        mfccs = np.mean(librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13).T, axis=0)
+        chroma = np.mean(librosa.feature.chroma_stft(y=y, sr=sr).T, axis=0)
+        spectral_contrast = np.mean(librosa.feature.spectral_contrast(y=y, sr=sr).T, axis=0)
+        zero_crossings = np.mean(librosa.feature.zero_crossing_rate(y).T, axis=0)
+        tempo, _ = librosa.beat.beat_track(y=y, sr=sr)
+
+        # Menggabungkan semua fitur
+        features = np.hstack([mfccs, chroma, spectral_contrast, zero_crossings, tempo])
+        return features
+    except Exception as e:
+        print(f"Error extracting features: {e}")
+        return None
+
+
+@app.route('/', methods=['GET', 'POST'])
+def index():
+    if request.method == 'POST':
+        # Periksa apakah file diunggah
+        if 'file' not in request.files:
+            return redirect(request.url)
+        file = request.files['file']
+        if file.filename == '':
+            return redirect(request.url)
+
+        # Simpan file ke folder yang ditentukan
+        file_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)
+        file.save(file_path)
+
+        # Periksa format file
+        if file.filename.lower().endswith('.mp3'):
+            # Konversi MP3 ke WAV
+            file_path_wav = convert_mp3_to_wav(file_path)
+            if file_path_wav is None:
+                return "Konversi MP3 ke WAV gagal. Pastikan file yang diunggah valid."
+            file_path = file_path_wav  # Gunakan file WAV untuk proses berikutnya
+
+        # Ekstraksi fitur dari file yang diunggah
+        features = extract_features(file_path)
+        if features is None:
+            return "Ekstraksi fitur gagal. Coba unggah file lain."
+
+        # Normalisasi fitur menggunakan scaler
+        features_scaled = scaler.transform([features])
+
+        # Prediksi genre menggunakan model
+        prediction = model.predict(features_scaled)
+        predicted_genre = genres[np.argmax(prediction)]
+
+        # Hapus file WAV setelah 30 detik
+        delete_file_after_delay(file_path, delay=30)
+
+        # Kembalikan hasil prediksi
+        return render_template('index.html', file_path=file_path, prediction=predicted_genre)
+
+    return render_template('index.html')
+
+
+if __name__ == '__main__':
+    app.run(debug=True)

model_code1.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f48886d66143f95bb2316e1df8b9d94367f7d5f14761ed8f55cccb883ad90af0
+size 8825044

requirements.txt

@@ -0,0 +1,6 @@
+Flask==3.1.0
+librosa==0.10.2.post1
+numpy==2.2.0
+scikit_learn==1.6.0
+tensorflow==2.18.0
+tensorflow_intel==2.18.0

scaler.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3ff5d059ce0b0a9600bf26b2d5b673e47a18a2101fb01d18cf0ec150181c4ac0
+size 1274

static/uploads/That's the One - Ryan McCaffreyGo By Ocean.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a44051ade58e941318b3ba736b5a82e6db2c00d7ab7bb88c9c7de7326e34a4ff
+size 8322649

templates/index.html

@@ -0,0 +1,77 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Music Genre Classification</title>
+    <!-- Bootstrap CSS -->
+    <link 
+        href="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0-alpha3/dist/css/bootstrap.min.css" 
+        rel="stylesheet"
+    >
+</head>
+<body class="bg-light">
+
+    <div class="container mt-5">
+        <!-- Header -->
+        <div class="text-center mb-4">
+            <h1 class="display-5 fw-bold">Music Genre Classification</h1>
+            <p class="lead text-secondary">Upload your music file (wav/mp3) and discover its genre!</p>
+        </div>
+
+        <!-- Upload Form -->
+        <div class="card shadow p-4">
+            <form action="/" method="post" enctype="multipart/form-data">
+                <div class="mb-3">
+                    <label for="file" class="form-label fw-bold">Upload a music file</label>
+                    <input type="file" id="file" name="file" class="form-control" accept=".wav,.mp3" onchange="previewAudio(event)">
+                </div>
+
+                <!-- Audio Player -->
+                <div class="mb-3" id="audioPlayerContainer" style="display: none;">
+                    <label class="form-label fw-bold">Preview:</label>
+                    <audio id="audioPlayer" controls class="w-100">
+                        <source id="audioSource" type="audio/wav">
+                        Your browser does not support the audio element.
+                    </audio>
+                </div>
+
+                <!-- Submit Button -->
+                <div class="d-grid">
+                    <button type="submit" class="btn btn-primary btn-lg">Submit</button>
+                </div>
+            </form>
+        </div>
+
+        <!-- Prediction Result -->
+        {% if file_path %}
+        <div class="card shadow mt-4 p-4">
+            <h4 class="fw-bold">Uploaded File:</h4>
+            <audio controls class="w-100 mb-3">
+                <source src="{{ file_path }}" type="audio/wav">
+                Your browser does not support the audio element.
+            </audio>
+            <h4 class="fw-bold">Predicted Genre:</h4>
+            <p class="fs-4 text-success"><strong>{{ prediction }}</strong></p>
+        </div>
+        {% endif %}
+    </div>
+
+    <!-- Bootstrap JS Bundle with Popper -->
+    <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0-alpha3/dist/js/bootstrap.bundle.min.js"></script>
+    <script>
+        function previewAudio(event) {
+            const file = event.target.files[0];
+            if (file) {
+                const audioPlayer = document.getElementById('audioPlayer');
+                const audioSource = document.getElementById('audioSource');
+                const audioPlayerContainer = document.getElementById('audioPlayerContainer');
+                
+                audioSource.src = URL.createObjectURL(file);
+                audioPlayerContainer.style.display = 'block';
+                audioPlayer.load();
+            }
+        }
+    </script>
+</body>
+</html>